With the rapid development of the Internet, search products and technologies have gained increasing popularity. Existing search products all have a search prompting function, that is, when a user enters a keyword into a search text box, terms that match the search keyword will appear in a drop-down list below the search text box for the user to select, facilitating the operation of the user.
Therefore, how to design a search prompting system that can maximize user satisfaction and convenience is a difficult problem for developers. In the existing technology, a search prompting system is evaluated by using an evaluation method, for example, according to click through rates of suggested search keywords, where the click through rate is the number of clicks on a keyword in the search prompting system divided by the number of impressions of the keyword in the search prompting system; or according to suggestion coverage rates of suggested search keywords, that is, a proportion of a keyword entered by a user that can be covered in the search prompting system.
However, both the above two evaluation methods have some defects: The implementation of the first evaluation method requires high costs because the number of impressions and the number of clicks of the search prompting system are continuously recorded. Although the second evaluation method is easy to implement, suggestion coverage efficiencies of different keywords vary significantly, making it difficult to obtain an accurate estimated value.